The replicator dynamics for age structured populations
نویسندگان
چکیده
1 Abstract In this paper is presented the new modelling framework combining the repli-cator dynamics (which is the standard model of the frequency dependent selection) with the Leslie Matrix model of the age-structured population. Firstly the continuous version of the discrete Leslie Matrix model is derived. It is shown that Euler–Lotka equation is satisfied when new model reaches the steady state (ie. stable related frequencies between the age classes). Due to the long expected lifespan of an individual in comparison with the ecological timescale, the real life model should contain a large number of equations. This problem is solved by the introduction of the large age classes concept. The underlying assumption is that within a single large age class the individuals do not differ in the demographic parameters (fertility and mortality). Then according to this result, a more complex model containing different individual strategies is presented. The methodology of the multipopulation games is used for derivation of two, mutually equivalent systems of equations. First contains equations describing the evolution of the strategy frequencies in the whole population completed by subsystems of equations describing the evolution of the age structure for each strategy. Second system contains equations describing the changes of general populations age structure, completed with subsystems of equations describing the selection of the strategies within each age class.
منابع مشابه
Evolutionary games on networks and payoff invariance under replicator dynamics
The commonly used accumulated payoff scheme is not invariant with respect to shifts of payoff values when applied locally in degree-inhomogeneous population structures. We propose a suitably modified payoff scheme and we show both formally and by numerical simulation, that it leaves the replicator dynamics invariant with respect to affine transformations of the game payoff matrix. We then show ...
متن کاملEvolutionary Game in a Single Hub Structure
In this paper, we investigate the evolutionary game theory on a simplest heterogeneous network-a single hub structure. In order to describe the dynamics on structured populations, we firstly give a general form of a spatial replicator equation. Then according to it, the evolutionary equations describing the evolution of two strategies (cooperation and defection) are derived explicitly and the d...
متن کاملLearning in Networked Interactions: A Replicator Dynamics Approach
Many real-world scenarios can be modelled as multi-agent systems, where multiple autonomous decision makers interact in a single environment. The complex and dynamic nature of such interactions prevents hand-crafting solutions for all possible scenarios, hence learning is crucial. Studying the dynamics of multi-agent learning is imperative in selecting and tuning the right learning algorithm fo...
متن کاملThe \sigma law of evolutionary dynamics in community-structured populations
Evolutionary game dynamics in finite populations provides a new framework to understand the selection of traits with frequency-dependent fitness. Recently, a simple but fundamental law of evolutionary dynamics, which we call σ law, describes how to determine the selection between two competing strategies: in most evolutionary processes with two strategies, A and B, strategy A is favored over B ...
متن کاملEvolutionary game dynamics in finite populations with strong selection and weak mutation.
We study stochastic game dynamics in finite populations. To this end we extend the classical Moran process to incorporate frequency-dependent selection and mutation. For 2 x 2 games, we give a complete analysis of the long-run behavior when mutation rates are small. For 3 x 3 coordination games, we provide a simple rule to determine which strategy will be selected in large populations. The expe...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2013